CN105956875A - Method and system for assessing agricultural scientific and technological achievements on the basis of big data and market price matching - Google Patents
Method and system for assessing agricultural scientific and technological achievements on the basis of big data and market price matching Download PDFInfo
- Publication number
- CN105956875A CN105956875A CN201610252085.1A CN201610252085A CN105956875A CN 105956875 A CN105956875 A CN 105956875A CN 201610252085 A CN201610252085 A CN 201610252085A CN 105956875 A CN105956875 A CN 105956875A
- Authority
- CN
- China
- Prior art keywords
- factor
- estimated
- correction factor
- comparable property
- characteristic
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0206—Price or cost determination based on market factors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/951—Indexing; Web crawling techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Mining
Abstract
The invention provides a method and system for assessing agricultural scientific and technological achievements on the basis of big data and market price matching. The method comprises steps of: acquiring primary data of an agricultural scientific and technological achievement by using network big data as a data source; and acquiring a final assessment result of a case to be assessed by using a preset market price matching method. The method assesses the price of the agricultural scientific and technological achievement in combination with the big data as a data support and the improved market price matching method, and provides a price reference for the transaction of agricultural scientific and technological achievements.
Description
Technical field
The present invention relates to big data and agricultural economy technical field, particularly relate to a kind of based on big number
According to the agricultural science and technology achievement valuation methods mated with market price and system.
Background technology
At present, prior art provides a kind of industry scientific and technological achievement property transaction platform, can play big
Data kind industry scientific and technological achievement information cloud platform feature；Prior art additionally provides a kind of Jing-jin-ji region section
The big data handling system of skill achievement customization service platform, to Beijing-tianjin-hebei Region scientific and technological achievement output
With being collected and analyzing of demand data；Prior art also utilizes automatic Searching, information
System customization technology, automatic Summarization Technique construct transformation of scientific and technical result dynamic information retrieval platform,
Achieve multidate information to mate with Search Requirement；Prior art also applies big data, Internet of Things etc.
Integration ofTechnology agricultural industry information public service platform；And, the most again by data mining technology,
Search technique is for the value assessment of the technology such as core patent.
Its essence of the translation of scientific and technological achievements in agriculture into productive forces is exactly the transaction of agricultural science and technology achievement, and supply and demand is double
During side's difference in agricultural science and technology achievement transaction value is Transformation of Agricultural Sci-Tech Achievements
One big obstacle.The price of agricultural science and technology achievement is seldom estimated by prior art, the biggest portion
Dividing research is all that the level to agricultural science and technology achievement is evaluated.
In consideration of it, how agricultural science and technology achievement is carried out the assessment of price, being effectively
The transaction of agricultural science and technology achievement provides price to solve the technical problem that with reference to becoming to be presently required.
Summary of the invention
For solving above-mentioned technical problem, the present invention provides a kind of and mates with market price based on big data
Agricultural science and technology achievement valuation methods and system, by with big data for data support combine improve
The market price matching method agricultural science and technology achievement is carried out the assessment of price, it is possible to effectively for agriculture
The transaction of industry scientific and technological achievement provides price reference.
First aspect, the present invention provides a kind of agricultural science and technology mated with market price based on big data to become
Really valuation methods, including:
With the big data of network as data source, obtain the primary data of target agricultural science and technology achievement；
Utilize and preset market price matching process, obtain the final rating result of example to be estimated.
Alternatively, market price matching process is preset in described utilization, obtains the final of example to be estimated
Rating result, including:
According to default comparable property alternative condition, select multiple than real in described primary data
Example；
Obtain the approach degree of example to be estimated and the plurality of comparable property, and to the approach degree obtained
It is ranked up according to descending order, it is thus achieved that ranking results；
Obtain to treat and estimate example and the marking value of each characteristic factor of all comparable property and each
The weight that characteristic factor is corresponding, and according to described marking value and weight, obtain each characteristic factor
Correction factor；
According to described ranking results, the correction factor obtained is carried out reasonability check；
According to the correction factor of each characteristic factor after checking, treat the transaction value estimating example
It is modified；
According to revised multiple prices with revise after weight corresponding to each price, obtain and wait to estimate
The final rating result of example.
Alternatively, described with the big data of network as data source, obtain target agricultural science and technology achievement
Primary data, including:
With the big data of network as data source, carry out coupling search according to target limitation attribute condition,
Obtain the primary data of target agricultural science and technology achievement；
Wherein, described target limitation attribute condition, including: application, application and pass
Key technology point.
Alternatively, described default comparable property alternative condition, including: it is in the same market supply and demand
Circle, purposes is identical, and type is identical, the exchange hour transaction examples less than a year.
Alternatively, the described approach degree obtaining example to be estimated and the plurality of comparable property, including:
According to the first formula, obtain the approach degree of example to be estimated and the plurality of comparable property；
Wherein, described first formula is:
σi(Ai, B) and=fi[μA(xi)∧μB(xi)]/[μA(xi)∨μB(xi)]
Wherein, σi(Ai, B) and for example B to be estimated and comparable property AiApproach degree, σi(Ai,B)
∈ [0,1]；μA(xi) it is i-th comparable property AiCharacteristic vector, μA(xi)=(ti1,ti2,ti3……tin),
tijFor the degree of membership of the characteristic factor j of comparable property i, j=1,2 ..., n；μB(xi) for example to be estimated
The characteristic vector of B, μB(xi)=(t1*,t2*…..tn*), tj* for the characteristic factor j of example B to be estimated
Degree of membership, j=1,2 ..., n；fiWeights for i-th factor.
Alternatively, the described approach degree to obtaining is ranked up according to descending order, obtains
Obtain ranking results, including:
The approach degree obtained is ranked up, when approach degree is identical, utilizes fuzzy relation coefficient
TxiIt is ranked up according to descending order；
Wherein, TxiBeing calculated by the second formula, described second formula is:
Txi=∑ tij/max∑tij。
Alternatively, described according to described marking value and weight, obtain the correction of each characteristic factor
Coefficient, including:
According to described marking value and weight, by the 3rd formula, obtain repairing of each characteristic factor
Positive coefficient；
Wherein, described 3rd formula is:
ki=∑ Sj* fj/∑SijFj,
kiFor individual factor correction factor；SijMarking for i-th comparable property jth factor
Value；fjFor the weight of jth factor, ∑ fj=1；Sj* beating for example jth factor to be estimated
Score value.
Alternatively, described according to described ranking results to obtain correction factor carry out reasonability school
Core, including:
If the correction factor that descending ranking results is corresponding be ascending and obtain each
The domain of walker of correction factor is less than predetermined threshold value, it is determined that the correction factor of acquisition is reasonable
Property；
If the domain of walker of each correction factor obtained exceedes predetermined threshold value, then return described according to
Preset comparable property alternative condition, described primary data selects the step of multiple comparable property
Reselect comparable property, or return described acquisition and treat and estimate example and all comparable property are every
The weight that the marking value of one characteristic factor is corresponding with each characteristic factor, and be worth according to described marking
And weight, the step of the correction factor obtaining each characteristic factor reacquires each characteristic factor
Correction factor, until the domain of walker of each correction factor obtained is less than predetermined threshold value.
Alternatively, the described correction factor according to each characteristic factor after checking, treat and estimate reality
The transaction value of example is modified, including:
According to the correction factor of each characteristic factor after checking, by the 4th formula, treat and estimate
The transaction value of example is modified；
Wherein, described 4th formula is:
P=P1×k1×k2×……×kn,
P is the revised price of example to be estimated, P1For the transaction value before example correction to be estimated,
k1,k2…knCorrection factor for each characteristic factor；
And/or,
Described according to revised multiple prices with revise after weight corresponding to each price, obtain
The final rating result of example to be estimated, including:
According to revised multiple prices with revise after weight corresponding to each price, by the 5th
Formula, obtains the final rating result of example to be estimated；
Wherein, described 5th formula is:
P '=∑ Pn*fn,
PnFor the revised rate of comparable property, fnFor PnCorresponding weight, ∑ fn=1, P ' be
The final rating result of example to be estimated.
Second aspect, the present invention provides a kind of agricultural science and technology mated with market price based on big data to become
Really appraisal system, including:
Data acquisition module, for the big data of network as data source, obtains target agricultural science and technology
The primary data of achievement；
Rating result acquisition module, is used for utilizing default market price matching process, obtains and wait to estimate
The final rating result of example.
As shown from the above technical solution, the agriculture section mated with market price based on big data of the present invention
Skill achievement valuation methods and system, can avoid the too much subjective error artificially participating in bringing, with
The big data of network are data source, by screening, then use market price Matching Model to carry out point
Analysis, it is possible to ensure that the price of the agricultural science and technology achievement obtained, without departing from market, has more and refers to
Property.
Accompanying drawing explanation
The agriculture section mated with market price based on big data that Fig. 1 provides for one embodiment of the invention
The schematic flow sheet of skill achievement valuation methods；
The agriculture section mated with market price based on big data that Fig. 2 provides for one embodiment of the invention
The structural representation of skill achievement appraisal system.
Detailed description of the invention
For making the purpose of the embodiment of the present invention, technical scheme and advantage clearer, below will knot
Close the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear,
Complete description, it is clear that described embodiment is only a part of embodiment of the present invention, and
It is not all, of embodiment.Based on embodiments of the invention, those of ordinary skill in the art are not having
Have and make the every other embodiment obtained under creative work premise, broadly fall into the present invention
The scope of protection.
Fig. 1 shows the agriculture mated based on big data that one embodiment of the invention provides with market price
The schematic flow sheet of industry scientific and technological achievement valuation methods, as it is shown in figure 1, the present embodiment based on greatly
The agricultural science and technology achievement valuation methods that data are mated with market price, including:
101, with the big data of network as data source, the first progression of target agricultural science and technology achievement is obtained
According to.
In a particular application, described step 101, may include that
With the big data of network as data source, carry out coupling search according to target limitation attribute condition,
Obtain the primary data of target agricultural science and technology achievement；
Wherein, described target limitation attribute condition, including: application, application and pass
Key technology point.
102, utilizing default market price matching process, obtain example to be estimated finally evaluates knot
Really.
In a particular application, described step 102, the step not shown in figure can be included
102a-102f:
102a, according to default comparable property alternative condition, select multiple in described primary data
Comparable property.
Wherein, described default comparable property alternative condition, it may include: it is in the same market supply and demand
Circle, purposes is identical, and type is identical, the exchange hour transaction examples etc. less than a year.So
Alternative condition can ensure that the comparable property chosen has the strongest operability relative to skeleton object
It will be appreciated that preset the selection course of comparable property in market price matching process it is exactly
The process of com-parison and analysis, enters transaction examples according to individual factor and regional factor with appraisal object
The comparison of row each side, on existing data base, the example of the right maximum of selector, comparable
The correct selection of example is to preset the essential step that market price matching process realizes.
102b, obtain the approach degree of example to be estimated and the plurality of comparable property, and to obtaining
Approach degree is ranked up according to descending order, it is thus achieved that ranking results.
In a particular application, described step 102b " obtains example to be estimated with the plurality of
The approach degree of comparable property ", may include that
According to the first formula, obtain the approach degree of example to be estimated and the plurality of comparable property；
Wherein, described first formula is:
σi(Ai, B) and=fi[μA(xi)∧μB(xi)]/[μA(xi)∨μB(xi)]
Wherein, σi(Ai, B) and for example B to be estimated and comparable property AiApproach degree, σi(Ai,B)
∈ [0,1]；μA(xi) it is i-th comparable property AiCharacteristic vector, μA(xi)=(ti1,ti2,ti3……tin),
tijFor the degree of membership of the characteristic factor j of comparable property i, j=1,2 ..., n；μB(xi) for example to be estimated
The characteristic vector of B, μB(xi)=(t1*,t2*…..tn*), tj* for the characteristic factor j of example B to be estimated
Degree of membership, j=1,2 ..., n；fiWeights for i-th factor.
It will be appreciated that so-called approach degree, refer to journey near one another between two fuzzy subsets
Degree, approach degree should be in [0,1] interval interior value.Object is the most close, and approach degree is the biggest.Work as patch
When recency is equal to 1, then two fuzzy subsets fit completely, the most close；When approach degree etc.
In 0 time, do not press close to.Sort according to the size of approach degree simultaneously, can be by sorting
Check correction factor size in example correction the most reasonable.
In a particular application, in described step 102b " to obtain approach degree according to by greatly
It is ranked up to little order, it is thus achieved that ranking results ", may include that
The approach degree obtained is ranked up, when approach degree is identical, utilizes fuzzy relation coefficient
TxiIt is ranked up according to descending order；
Wherein, TxiBeing calculated by the second formula, described second formula is:
Txi=∑ tij/max∑tij。
It should be noted that approach degree the biggest example comparability is the strongest during example screens.
During revising, approach degree is the biggest, revises degree the least.
102c, obtain treat estimate example and the marking value of each characteristic factor of all comparable property and
The weight that each characteristic factor is corresponding, and according to described marking value and weight, obtain each feature
The correction factor of factor.
Wherein, the weight that each characteristic factor is corresponding reflects that each characteristic factor is to comparable property
Influence degree.
In a particular application, in described step 102c " according to described marking value and weight,
Obtain the correction factor of each characteristic factor ", may include that
According to described marking value and weight, by the 3rd formula, obtain repairing of each characteristic factor
Positive coefficient；
Wherein, described 3rd formula is:
ki=∑ Sj* fj/∑SijFj,
kiFor individual factor correction factor；SijMarking for i-th comparable property jth factor
Value；fjFor the weight of jth factor, ∑ fj=1；Sj* beating for example jth factor to be estimated
Score value.
It should be noted that before performing step 102a, can first select achievement to be estimated (i.e.
Example to be estimated) purposes, according to purposes select affect its value principal element, according to these
The description of factor inputs example to be estimated and comparable property property value respectively and obtains the person in servitude of its correspondence
The characteristic vector that genus degree and degree of membership are constituted.
102d, according to described ranking results to obtain correction factor carry out reasonability check.
In a particular application, described step 102d, may include that
If the correction factor that descending ranking results is corresponding be ascending and obtain each
The domain of walker of correction factor is less than predetermined threshold value, it is determined that the correction factor of acquisition is reasonable
Property；
If the domain of walker of each correction factor obtained exceedes predetermined threshold value, then return described according to
Preset comparable property alternative condition, described primary data selects the step of multiple comparable property
Reselect comparable property, or return described acquisition and treat and estimate example and all comparable property are every
The weight that the marking value of one characteristic factor is corresponding with each characteristic factor, and be worth according to described marking
And weight, the step of the correction factor obtaining each characteristic factor reacquires each characteristic factor
Correction factor, until the domain of walker of each correction factor obtained is less than predetermined threshold value.
It will be appreciated that comparable property factor correction is the emphasis place of market method, it is can body
Now evaluate the stage of level.Comparable property and the feelings of achievement to be assessed are found in it is critical only that of revising
Condition contrasts, and finds the impact on being worth of difference place and this species diversity.Comparable property factor is repaiied
Just including the correction of multiclass factor.To total update the system by sorting from small to large, for revising school
Core is used.The domain of walker of each correction factor is 20%, and total correction factor domain of walker does not allows
More than 30%.If total correction factor overruns, the most again revise or abandon again to choose comparable
Example, until total amplitude of revising is in allowed band.
It will be appreciated that described step 102d is the person in servitude according to example to be assessed and comparable property
Genus degree characteristic vector calculates both approach degrees, sorts by the size of approach degree, and approach degree is more
Big correction factor is the least, checks the reasonability of correction with this.
102e, according to the correction factor of each characteristic factor after checking, treat the friendship estimating example
Easily price is modified.
In a particular application, described step 102e, may include that
According to the correction factor of each characteristic factor after checking, by the 4th formula, treat and estimate
The transaction value of example is modified；
Wherein, described 4th formula is:
P=P1×k1×k2×……×kn,
P is the revised price of example to be estimated, P1For the transaction value before example correction to be estimated,
k1,k2…knCorrection factor for each characteristic factor.
102f, according to revised multiple prices with revise after weight corresponding to each price, obtain
Take the final rating result of example to be estimated.
Wherein, the weight that revised each price is corresponding reflects the weight of revised each price
Want degree.
In a particular application, described step 102f, may include that
According to revised multiple prices with revise after weight corresponding to each price, by the 5th
Formula, obtains the final rating result of example to be estimated；
Wherein, described 5th formula is:
P '=∑ Pn*fn,
PnFor the revised rate of comparable property, fn is the weight that Pn is corresponding, and ∑ fn=1, P ' are
The final rating result of example to be estimated.
During it will be appreciated that each price that correction is gone out comprehensively becomes a price, it is contemplated that every
The significance level of individual price is different, can first give the weight that each price is different, the most comprehensively ask
Go out a price.Generally for the price revised out with the appraisal most similar comparable property of object,
Give maximum flexible strategy, otherwise, give minimum flexible strategy.
It will be appreciated that described step 102e can be used for price correction when transaction examples is put in storage.
The agricultural science and technology achievement valuation methods mated with market price based on big data of the present embodiment, can
By processor realizes, the too much subjective error artificially participating in bringing can be avoided, with network
Big data are data source, by screening, then use market price Matching Model to be analyzed,
Ensure that the price of the agricultural science and technology achievement obtained, without departing from market, has more referring to property.
Fig. 2 shows the agricultural mated based on big data that one embodiment of the invention provides with market price
The structural representation of scientific and technological achievement appraisal system, as in figure 2 it is shown, the present embodiment based on big number
According to the agricultural science and technology achievement appraisal system mated with market price, including: data acquisition module 21 with estimate
Valency result acquisition module 22；
Data acquisition module 21, for the big data of network as data source, obtains target agricultural
The primary data of scientific and technological achievement；
Rating result acquisition module 22, is used for utilizing default market price matching process, obtains
The final rating result of example to be estimated.
In a particular application, described rating result acquisition module 22, it may include not shown in figure:
First acquiring unit, select unit, second acquisition unit, the 3rd acquiring unit, check unit,
Amending unit and the 4th acquiring unit；
First acquiring unit, for the big data of network as data source, obtains target agricultural science and technology
The primary data of achievement；
Select unit, for according to default comparable property alternative condition, in described primary data
Select multiple comparable property；
Second acquisition unit, for obtaining the approach degree of example to be estimated and the plurality of comparable property,
And the approach degree obtained is ranked up according to descending order, it is thus achieved that ranking results；
3rd acquiring unit, treat for acquisition estimate example and each feature of all comparable property because of
The weight that plain marking value is corresponding with each characteristic factor, and according to described marking value and weight,
Obtain the correction factor of each characteristic factor；
Check unit, for the correction factor obtained being carried out reasonability according to described ranking results
Check；
Amending unit, for the correction factor according to each characteristic factor after checking, treats and estimates
The transaction value of example is modified；
4th acquiring unit, for according to each price pair after revised multiple prices and correction
The weight answered, obtains the final rating result of example to be estimated.
Wherein, the weight that each characteristic factor is corresponding reflects that each characteristic factor is to comparable property
Influence degree, the weight of the weight revised each price of reflection that revised each price is corresponding
Want degree.
It will be appreciated that the work process of system described in the present embodiment mainly can include following
Stage:
One, staff is by agricultural science and technology achievement information keywords Message Entry System bag to be evaluated
Include: application, application, key technology, market supply and demand circle, purposes, achievement type
Deng.
Two, data acquisition phase.This stage this method, with the big data of network as source data, is being received
Automatically acquisition can be extracted by big data retrieval relevant to product to be assessed after assessing instruction
The data of agricultural science and technology achievement and Transaction Information, be primary data.
Three, market price coupling evaluation stage.When primary data obtains complete, and system can be automatically
Call market price Matching Model to be estimated.
Four, the presenting and show of result, after when market price coupling, evaluation stage operated,
Result is presented to user in visual mode.
System described in the present embodiment may be used for performing said method embodiment, its principle and skill
Art effect is similar to, and here is omitted.
It should be noted that for system embodiment, owing to it is basic with embodiment of the method
Similar, so describe is fairly simple, relevant part sees the part explanation of embodiment of the method i.e.
Can.
The agricultural science and technology achievement appraisal system mated with market price based on big data of the present embodiment, can
Avoid the too much subjective error artificially participating in bringing, with the big data of network as data source, pass through
Screening, then uses market price Matching Model to be analyzed, it is possible to ensure the agriculture section obtained
The price of skill achievement, without departing from market, has more referring to property.
One of ordinary skill in the art will appreciate that: realize the whole of above-mentioned each method embodiment or
Part steps can be completed by the hardware that programmed instruction is relevant.Aforesaid program can store
In a computer read/write memory medium.This program upon execution, performs to include above-mentioned each side
The step of method embodiment；And aforesaid storage medium includes: ROM, RAM, magnetic disc or
The various medium that can store program code such as CD.
It is last it is noted that various embodiments above is only in order to illustrate technical scheme,
It is not intended to limit；Although the present invention being described in detail with reference to foregoing embodiments,
It will be understood by those within the art that: it still can be to described in foregoing embodiments
Technical scheme modify, or the most some or all of technical characteristic carried out equivalent replace
Change；And these amendments or replacement, do not make the essence of appropriate technical solution depart from the present invention each
The scope of embodiment technical scheme.
Claims (10)
1. the agricultural science and technology achievement valuation methods mated with market price based on big data, it is special
Levy and be, including:
With the big data of network as data source, obtain the primary data of target agricultural science and technology achievement；
Utilize and preset market price matching process, obtain the final rating result of example to be estimated.
Method the most according to claim 1, it is characterised in that city is preset in described utilization
Field prices match method, obtains the final rating result of example to be estimated, including:
According to default comparable property alternative condition, select multiple than real in described primary data
Example；
Obtain the approach degree of example to be estimated and the plurality of comparable property, and to the approach degree obtained
It is ranked up according to descending order, it is thus achieved that ranking results；
Obtain to treat and estimate example and the marking value of each characteristic factor of all comparable property and each
The weight that characteristic factor is corresponding, and according to described marking value and weight, obtain each characteristic factor
Correction factor；
According to described ranking results, the correction factor obtained is carried out reasonability check；
According to the correction factor of each characteristic factor after checking, treat the transaction value estimating example
It is modified；
According to revised multiple prices with revise after weight corresponding to each price, obtain and wait to estimate
The final rating result of example.
Method the most according to claim 1, it is characterised in that described with the big number of network
According to for data source, obtain the primary data of target agricultural science and technology achievement, including:
With the big data of network as data source, carry out coupling search according to target limitation attribute condition,
Obtain the primary data of target agricultural science and technology achievement；
Wherein, described target limitation attribute condition, including: application, application and pass
Key technology point.
Method the most according to claim 2, it is characterised in that described default than real
Example alternative condition, including: being in same market supply and demand circle, purposes is identical, and type is identical, hands over
The easily time transaction examples less than a year.
Method the most according to claim 2, it is characterised in that described obtain reality to be estimated
Example and the approach degree of the plurality of comparable property, including:
According to the first formula, obtain the approach degree of example to be estimated and the plurality of comparable property；
Wherein, described first formula is:
σi(Ai, B) and=fi[μA(xi)∧μB(xi)]/[μA(xi)∨μB(xi)]
Wherein, σi(Ai, B) and for example B to be estimated and comparable property AiApproach degree, σi(Ai,B)
∈ [0,1]；μA(xi) it is i-th comparable property AiCharacteristic vector, μA(xi)=(ti1,ti2,ti3……tin),
tijFor the degree of membership of the characteristic factor j of comparable property i, j=1,2 ..., n；μB(xi) for example to be estimated
The characteristic vector of B, μ B (xi)=(t1*,t2*…..tn*), tj* for the characteristic factor j of example B to be estimated
Degree of membership, j=1,2 ..., n；fiWeights for i-th factor.
Method the most according to claim 5, it is characterised in that the described patch to obtaining
Recency is ranked up according to descending order, it is thus achieved that ranking results, including:
The approach degree obtained is ranked up, when approach degree is identical, utilizes fuzzy relation coefficient
TxiIt is ranked up according to descending order；
Wherein, TxiBeing calculated by the second formula, described second formula is:
Txi=∑ tij/max∑tij。
Method the most according to claim 2, it is characterised in that beat described in described basis
Score value and weight, obtain the correction factor of each characteristic factor, including:
According to described marking value and weight, by the 3rd formula, obtain repairing of each characteristic factor
Positive coefficient；
Wherein, described 3rd formula is:
ki=∑ Sj* fj/∑SijFj,
kiFor individual factor correction factor；SijMarking for i-th comparable property jth factor
Value；fjFor the weight of jth factor, ∑ fj=1；Sj* beating for example jth factor to be estimated
Score value.
Method the most according to claim 2, it is characterised in that described according to described row
Sequence result carries out reasonability check to the correction factor obtained, including:
If the correction factor that descending ranking results is corresponding be ascending and obtain each
The domain of walker of correction factor is less than predetermined threshold value, it is determined that the correction factor of acquisition is reasonable
Property；
If the domain of walker of each correction factor obtained exceedes predetermined threshold value, then return described according to
Preset comparable property alternative condition, described primary data selects the step of multiple comparable property
Reselect comparable property, or return described acquisition and treat and estimate example and all comparable property are every
The weight that the marking value of one characteristic factor is corresponding with each characteristic factor, and be worth according to described marking
And weight, the step of the correction factor obtaining each characteristic factor reacquires each characteristic factor
Correction factor, until the domain of walker of each correction factor obtained is less than predetermined threshold value.
Method the most according to claim 2, it is characterised in that described according to check after
The correction factor of each characteristic factor, treat and estimate the transaction value of example and be modified, including:
According to the correction factor of each characteristic factor after checking, by the 4th formula, treat and estimate
The transaction value of example is modified；
Wherein, described 4th formula is:
P=P1×k1×k2×……×kn,
P is the revised price of example to be estimated, P1For the transaction value before example correction to be estimated,
k1,k2…knCorrection factor for each characteristic factor；
And/or,
Described according to revised multiple prices with revise after weight corresponding to each price, obtain
The final rating result of example to be estimated, including:
According to revised multiple prices with revise after weight corresponding to each price, by the 5th
Formula, obtains the final rating result of example to be estimated；
Wherein, described 5th formula is:
P '=∑ Pn*fn,
PnFor the revised rate of comparable property, fnFor PnCorresponding weight, ∑ fn=1, P ' be
The final rating result of example to be estimated.
10. the agricultural science and technology achievement appraisal system mated with market price based on big data, it is special
Levy and be, including:
Data acquisition module, for the big data of network as data source, obtains target agricultural science and technology
The primary data of achievement；
Rating result acquisition module, is used for utilizing default market price matching process, obtains and wait to estimate
The final rating result of example.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610252085.1A CN105956875A (en) | 2016-04-21 | 2016-04-21 | Method and system for assessing agricultural scientific and technological achievements on the basis of big data and market price matching |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610252085.1A CN105956875A (en) | 2016-04-21 | 2016-04-21 | Method and system for assessing agricultural scientific and technological achievements on the basis of big data and market price matching |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105956875A true CN105956875A (en) | 2016-09-21 |
Family
ID=56915017
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610252085.1A Pending CN105956875A (en) | 2016-04-21 | 2016-04-21 | Method and system for assessing agricultural scientific and technological achievements on the basis of big data and market price matching |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105956875A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109961326A (en) * | 2019-03-27 | 2019-07-02 | 廊坊新奥泛能网络科技服务有限公司 | The evaluation method and device of pipe network cost |
| WO2020007177A1 (en) * | 2018-07-05 | 2020-01-09 | 京东方科技集团股份有限公司 | Quotation method executed by computer, quotation device, electronic device and storage medium |
| CN111062585A (en) * | 2019-11-28 | 2020-04-24 | 重庆市科学技术研究院 | Scientific and technological product evaluation method and system based on big data platform |
| CN112435096A (en) * | 2020-11-30 | 2021-03-02 | 贵州电网有限责任公司 | Scientific and technological achievement and data resource property right transaction system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103543019A (en) * | 2013-10-28 | 2014-01-29 | 合肥英塔信息技术有限公司 | Method and system for quantifying evaluation and estimation of second-hand automobiles |
| CN203606141U (en) * | 2013-10-28 | 2014-05-21 | 程东 | A secondary-hand automobile quantification identification assessment system |
| CN103839166A (en) * | 2012-11-21 | 2014-06-04 | 索尼公司 | Method for acquisition and distribution of product price information |
| CN103838764A (en) * | 2012-11-26 | 2014-06-04 | 深圳市世纪光速信息技术有限公司 | Searching result correlation evaluating method and device |
| CN104517192A (en) * | 2014-12-29 | 2015-04-15 | 芜湖乐锐思信息咨询有限公司 | Intellectual property valuation system |
-
2016
- 2016-04-21 CN CN201610252085.1A patent/CN105956875A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103839166A (en) * | 2012-11-21 | 2014-06-04 | 索尼公司 | Method for acquisition and distribution of product price information |
| CN103838764A (en) * | 2012-11-26 | 2014-06-04 | 深圳市世纪光速信息技术有限公司 | Searching result correlation evaluating method and device |
| CN103543019A (en) * | 2013-10-28 | 2014-01-29 | 合肥英塔信息技术有限公司 | Method and system for quantifying evaluation and estimation of second-hand automobiles |
| CN203606141U (en) * | 2013-10-28 | 2014-05-21 | 程东 | A secondary-hand automobile quantification identification assessment system |
| CN104517192A (en) * | 2014-12-29 | 2015-04-15 | 芜湖乐锐思信息咨询有限公司 | Intellectual property valuation system |
Non-Patent Citations (4)
| Title |
|---|
| 吴士力 等: "《通俗模糊数学与程序设计》", 31 January 2008 * |
| 张昕 等: "区域存量房地产价格批量评估技术实证研究", 《科技创新导报》 * |
| 王铮铮 等: "《房地产估价理论与应用》", 31 March 2014 * |
| 聂艳 等: "《耕地质量评价理论与实践》", 31 May 2014 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020007177A1 (en) * | 2018-07-05 | 2020-01-09 | 京东方科技集团股份有限公司 | Quotation method executed by computer, quotation device, electronic device and storage medium |
| US11544751B2 (en) | 2018-07-05 | 2023-01-03 | Beijing Boe Technology Development Co., Ltd. | Quotation method executed by computer, quotation device, electronic device and storage medium |
| CN109961326A (en) * | 2019-03-27 | 2019-07-02 | 廊坊新奥泛能网络科技服务有限公司 | The evaluation method and device of pipe network cost |
| CN111062585A (en) * | 2019-11-28 | 2020-04-24 | 重庆市科学技术研究院 | Scientific and technological product evaluation method and system based on big data platform |
| CN112435096A (en) * | 2020-11-30 | 2021-03-02 | 贵州电网有限责任公司 | Scientific and technological achievement and data resource property right transaction system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zavadskas et al. | Selecting a contractor by using a novel method for multiple attribute analysis: Weighted Aggregated Sum Product Assessment with grey values (WASPAS-G) | |
| Baležentis et al. | MULTIMOORA-FG: a multi-objective decision making method for linguistic reasoning with an application to personnel selection | |
| CN106339756A (en) | Training data generation method and device and searching method and device | |
| CN110163258A (en) | A kind of zero sample learning method and system reassigning mechanism based on semantic attribute attention | |
| Zhang et al. | A quantitative approach to design alternative evaluation based on data-driven performance prediction | |
| CN105868847A (en) | Shopping behavior prediction method and device | |
| Zhao et al. | Modeling Stated preference for mobility-on-demand transit: a comparison of Machine Learning and logit models | |
| CN105956875A (en) | Method and system for assessing agricultural scientific and technological achievements on the basis of big data and market price matching | |
| CN110689091B (en) | Weak supervision fine-grained object classification method | |
| CN110413775A (en) | A kind of data label classification method, device, terminal and storage medium | |
| CN110599839A (en) | Online examination method and system based on intelligent paper grouping and text analysis review | |
| CN110210625A (en) | Modeling method, device, computer equipment and storage medium based on transfer learning | |
| Chi et al. | Development of a data mining-based analysis framework for multi-attribute construction project information | |
| CN109117872A (en) | A kind of user power utilization behavior analysis method based on automatic Optimal Clustering | |
| CN107609084A (en) | One kind converges convergent resource correlation method based on gunz | |
| Pujari et al. | Link prediction in complex networks by supervised rank aggregation | |
| CN107545038A (en) | A kind of file classification method and equipment | |
| CN106776950A (en) | A kind of field shoe impression mark decorative pattern image search method based on expertise guiding | |
| CN107451210A (en) | A kind of figure matching inquiry method based on inquiry relaxation result enhancing | |
| Viroonluecha et al. | Salary predictor system for thailand labour workforce using deep learning | |
| Drăgulescu et al. | Predicting assignment submissions in a multi-class classification problem | |
| CN110990662B (en) | Domain expert selection method based on citation network and scientific research cooperation network | |
| CN116595328B (en) | Knowledge-graph-based intelligent construction device and method for data scoring card model | |
| Keselman et al. | Optimizing Algorithms From Pairwise User Preferences | |
| Wati et al. | Evaluation of scholarly performance student using multi-criteria decision-making with objective weight |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160921 |